Nevin Manimala

Sleep. 2025 Aug 8:zsaf226. doi: 10.1093/sleep/zsaf226. Online ahead of print.

ABSTRACT

STUDY OBJECTIVES: Atrial fibrillation (AF) and obstructive sleep apnea (OSA) are interrelated conditions that substantially increase the risk of cardiovascular complications. However, concurrent detection of these conditions remains a critical unmet need in clinical practice. Current home sleep apnea test (HSAT) devices often fail to detect arrhythmias essential for diagnosing OSA-associated AF due to limited ECG monitoring capabilities, and their integration with continuous positive airway pressure (CPAP) data for treatment optimization remains underutilized.

METHODS: This study introduces SHHDeepNet, an advanced deep learning-based framework designed for the detection of OSA in patients with AF, leveraging enhanced features extracted from single-lead electrocardiogram (ECG) signals. The ECG signals were preprocessed and refined using reconstruction independent component analysis (RICA), which isolates statistically independent features for improved data representation. These features were subsequently classified using the customized SHHDeepNet architecture. SHHDeepNet utilizes advanced signal processing and deep learning techniques to enhance ECG-based detection of AF-associated OSA.

RESULTS: The framework was validated using overnight ECG recordings from 101 subjects derived from the Sleep Heart Health Study Visit 1 (SHHS1) database, encompassing 36 prevalent AF (PAF) cases, 25 incident AF (IAF) cases, and 40 OSA cases. Detection performance was evaluated through binary classification (AF AH vs. AF non-AH) and multi-class classification (AF AH, AF non-AH, non-AF AH, and non-AF non-AH). During 5-fold cross-validation (5fold-CV), the framework achieved a binary classification accuracy of 98.22%, sensitivity of 96.8%, specificity of 99%, and an area under the curve (AUC) of 0.9981. For multi-class classification, 5fold-CV yielded 98.36% accuracy, 97.14% sensitivity, 98.77% specificity, and an AUC of 0.9975. Validation using leave-one-subject-out cross-validation (LOSO-CV) achieved a binary classification accuracy of 86.42%, sensitivity of 79.4%, specificity of 90.2%, and an AUC of 0.9372. For multi-class classification under LOSO-CV, the average accuracy, sensitivity, and F1-score were 86.7%, 72.6%, and 0.7224, respectively. External validation was performed on a cohort of 123 subjects from the Osteoporotic Fractures in Men (MrOS) database, comprising 68 cases of PAF and 55 cases of OSA. The proposed method achieved a multi-class classification accuracy of 88.51%, sensitivity of 73.50%, specificity of 91.34%, and an AUC of 0.9363.

CONCLUSIONS: These findings underscore the significance of simultaneous detection of AF and OSA, providing a more comprehensive evaluation of cardiovascular health. The proposed SHHDeepNet framework offers a promising tool to support clinical decision-making, enhance management strategies, and improve patient outcomes by mitigating the risks associated with these conditions.

PMID:40795334 | DOI:10.1093/sleep/zsaf226

Int J Neuropsychopharmacol. 2025 Aug 8:pyaf059. doi: 10.1093/ijnp/pyaf059. Online ahead of print.

ABSTRACT

BACKGROUND: Ulotaront is an experimental antipsychotic for schizophrenia, but its optimal dose is unclear. This study aimed to evaluate dose-response relationships for efficacy and safety in people with schizophrenia.

METHOD: A systematic review of four databases (until January 22, 2025; INPLASY202510091) identified randomized clinical trials assessing ulotaront. Outcomes included efficacy, measured by changes in the Positive and Negative Syndrome Scale (PANSS) total score (primary outcome), positive and negative subdomains, and the Clinical Global Impression Scale-Severity (CGI-S), and safety, assessed by all-cause dropout (co-primary outcome, dropout due to adverse event, serious, non-serious, and specific adverse events. We employed one-stage dose-response meta-analysis (random-effects model) calculating standardized mean differences (SMDs) and risk ratios (RRs) with 95% confidence intervals (CIs).

RESULTS: Analysis of three randomized clinical trials (n=1,144) indicated that the 100 mg dose of ulotaront provided the greatest improvement in PANSS total score (SMD = -0.23 [95% CI: -0.43, -0.02]), PANSS positive symptom score (-0.30 [-0.70, 0.10]), and PANSS negative symptom score (-0.28 [-0.48, -0.08]). However, CGI-S scores did not exhibit a clear dose-response relationship. Regarding safety, all-cause dropout (RR at 100mg =1.10 [95% CI: 0.57, 2.12]), adverse event-related dropout, serious, non-serious, and most specific adverse events showed no significant dose-response relationship. The risk of anxiety-related adverse events was significantly higher than placebo at 50 mg and 75 mg doses (RR at 75mg =2.06 [95% CI: 1.11, 3.80]).

CONCLUSION: Ulotaront 100 mg appears greatest efficacy with favorable safety for acute schizophrenia. However, effect sizes were small, and higher ulotaront doses should be tested.

PMID:40795331 | DOI:10.1093/ijnp/pyaf059

J Med Internet Res. 2025 Aug 12;27:e70414. doi: 10.2196/70414.

ABSTRACT

BACKGROUND: Virtual care interventions have the potential to improve access to care and serial medication intensification for patients with chronic heart failure with reduced ejection fraction (HFrEF). However, concerns remain that these interventions might unintentionally create or widen existing disparities in care delivery and patient outcomes.

OBJECTIVE: This study aimed to characterize the health care use patterns of patients who have HFrEF, including specialty type and frequency of in-person and virtual visits.

METHODS: We conducted a retrospective cohort study of patients with HFrEF within a large health system. Inclusion criteria were patients alive with an ejection fraction ≤40% as of September 1, 2021, and at least one virtual or in-person outpatient visit to a primary care or cardiology clinician in the prior year. Descriptive statistics were used to evaluate baseline patient demographics and clinical use data and outcomes. Univariate analyses were performed both with virtual visits as a variable (received or did not receive) using the chi-square test for association and as a discrete outcome using the Wilcoxon rank-sum test to capture potentially important predictor variables that could influence use or frequency of using virtual visits. The primary outcome of interest was the odds of at least one virtual visit during the 1-year evaluation period from 2021 to 2022. Descriptive statistics were used to evaluate baseline patient demographics and care use. A logistic regression model was used to model at least one primary care or cardiology virtual visit.

RESULTS: A total of 8481 patients were included in the analysis. The mean age was 65.9 years (SD 15.1), 5672 (66.9%) patients were male and 6608 (77.9%) patients were non-Hispanic White. The majority of patients had no cardiology (7938/8481, 93.6%) or primary care (7955/8481, 93.8%) virtual visits during the evaluation period. Multivariable logistic regression showed significantly higher odds of having at least one virtual visit for patients with certain digital access-for example, email on file (odds ratio [OR] 9.3, P≤.001), cell phone on file (OR 2.9, P≤.001), and active electronic health record patient portal (OR 2.8, P≤.001)-than those without. Age, race, ethnicity, rurality, and Social Vulnerability Index were not associated with virtual visits.

CONCLUSIONS: Only a minority of patients with HFrEF were seen via virtual visits. Patients who regularly used digital technology were more likely to have virtual visits. Patients were more likely to be seen in a cardiology clinic than by a primary care provider. Although there was no evidence of an association between social determinants of health factors like race, ethnicity, or rurality with digital divide indicators, these findings should be interpreted with caution given the limitations of these data. Future studies should aim to replicate the findings of this study and explore ways to enhance the effective and equitable use of virtual visits.

PMID:40795329 | DOI:10.2196/70414

J Bone Miner Res. 2025 Aug 8:zjaf091. doi: 10.1093/jbmr/zjaf091. Online ahead of print.

ABSTRACT

The aim of this international meta-analysis was to quantify the predictive value of body mass index (BMI) for incident fracture and relationship of this risk with age, sex, follow-up time and bone mineral density (BMD). 1 667 922 men and women from 32 countries (63 cohorts), followed for a total of 16.0 million person-years were studied. 293 325 had femoral neck BMD measured (2.2 million person-years follow-up). An extended Poisson model in each cohort was used to investigate relationships between WHO-defined BMI categories (Underweight:<18.5 kg/m2; Normal:18.5-24.9 kg/m2; Overweight:25.0-29.9 kg/m2; Obese I:30.0-34.9 kg/m2; Obese II:≥35.0 kg/m2) and risk of incident osteoporotic, major osteoporotic and hip fracture (HF). Inverse-variance weighted β-coefficients were used to merge the cohort-specific results. For the subset with BMD available, in models adjusted for age and follow-up time, the hazard ratio (95%CI) for HF comparing underweight with normal weight was 2.35 (2.10-2.60) in women and for men was 2.45 (1.90-3.17). HF risk was lower in overweight and obese categories compared to normal weight [obese II vs normal: women 0.66 (0.55-0.80); men 0.91 (0.66-1.26). Further adjustment for femoral neck BMD T-score attenuated the increased risk associated with underweight [underweight vs normal: women 1.69 (1.47-1.96); men 1.46 (1.00-2.13)]. In these models, the protective effects of overweight and obesity were attenuated, and in both sexes the direction of association reversed to higher fracture risk in Obese II category [Obese II vs Normal: women 1.24 (0.97-1.58); men 1.70 (1.06-2.75)]. Results were similar for other fracture outcomes. Underweight is a risk factor for fracture in both men and women regardless of adjustment for BMD. However, whilst overweight/obesity appeared protective base models, they became risk factors after additional adjustment for femoral neck BMD, particularly in the Obese II category. This effect in the highest BMI categories was of greater magnitude in men than women. These results will inform the second iteration of FRAX.

PMID:40795319 | DOI:10.1093/jbmr/zjaf091

J Immunol. 2025 Aug 7:vkaf155. doi: 10.1093/jimmun/vkaf155. Online ahead of print.

ABSTRACT

Tumor clearance by T cells is impaired by insufficient tumor antigen recognition, insufficient tumor infiltration, and the immunosuppressive tumor microenvironment. Although targeted T cell therapy circumvents failures in tumor antigen recognition, suppression by the tumor microenvironment and failure to infiltrate the tumor can hinder tumor clearance. Checkpoint inhibitors (CPIs) promise to reverse T cell suppression and can be combined with bispecific antibody armed T cell (BAT) therapy to improve clinical outcomes. We hypothesize that adoptively transferred T cell function may be improved by the addition of CPIs if the inhibitory pathway is functionally active. This study develops a kinetic-dynamic model of killing of hormone receptor-positive breast cancer cells mediated by BATs using single-cell transcriptomic and temporal protein data to identify T cell phenotypes and quantify inhibitory receptor expression. LAG3, PD-1, and TIGIT were identified as inhibitory receptors expressed by cytotoxic effector CD8 BATs upon exposure to hormone receptor-positive breast cancer cell lines. These data were combined with real-time tumor cytotoxicity data in a multivariate statistical analysis framework to predict the relevant contributions of T cells expressing each receptor to tumor reduction. A mechanistic kinetic-dynamic mathematical model was developed and parametrized using protein expression and cytotoxicity data for in silico validation of the findings of the multivariate statistical analysis. The model corroborated the predictions of the multivariate statistical analysis which identified LAG3+ BATs as the primary effectors, while TIGIT expression dampened cytotoxic function. These results inform CPI selection for BATs combination therapy and provide a framework to maximize BATs antitumor function.

PMID:40795300 | DOI:10.1093/jimmun/vkaf155

J Proteome Res. 2025 Aug 12. doi: 10.1021/acs.jproteome.5c00297. Online ahead of print.

ABSTRACT

Over the past 30 years, software for searching tandem mass spectrometry data against a protein database has improved dramatically in speed and statistical power. However, existing tools can still struggle to analyze truly massive data sets when either the number of spectra or the number of proteins being analyzed grows too large. Here, we describe enhancements to the Tide search engine that allow it to handle data sets containing >10 million spectra and databases containing >7 billion peptides on commodity hardware. We demonstrate that the new Tide architecture is around 2-7 times faster than the previous version and is now comparable to MSFragger and Sage in speed while requiring much less memory. Tide is open source and is publicly available as precompiled binaries for Windows, Linux, and Mac.

PMID:40795295 | DOI:10.1021/acs.jproteome.5c00297

J Crohns Colitis. 2025 Aug 8:jjaf132. doi: 10.1093/ecco-jcc/jjaf132. Online ahead of print.

ABSTRACT

BACKGROUND AND AIMS: We investigated the correlations between patient-reported outcome measures (PROMs) and other measures of inflammatory bowel disease (IBD) activity.

METHODS: A systematic literature review was performed up to June 2022. Searches were conducted in PubMed, Scopus and Web of Science. A descriptive analysis was performed. The search protocol was registered in PROSPERO (CRD42022383899).

RESULTS: Nineteen studies assessed correlations between PROMs and clinical, endoscopic, and laboratory measures of disease activity in IBD. In Crohn’s disease (CD), weak positive correlations were reported for PROMs (e.g. the two-item patient reported outcome [PRO-2], mobile Health Index [mHI] for CD) and endoscopic scores, more often the Simple Endoscopic Score for CD (SES-CD). In ulcerative colitis (UC), PROMs like PRO-2, the Monitor IBD at Home rectal bleeding item and the mHI, showed weak-to-moderate correlations with the Mayo endoscopic subscore (MES). PROMs also demonstrated limited concordance with laboratory measures such as faecal calprotectin (FCP) and C-reactive protein (CRP) in both CD and UC. The substantial heterogeneity in study designs precluded a structured analysis.

CONCLUSIONS: Although current PROMs offer valuable complementary insights into IBD control from the patient’s perspective, they cannot replace objective measures of IBD activity. Future research should focus on refining PROMs and generating composite indices to improve their accuracy and usefulness.

PMID:40795293 | DOI:10.1093/ecco-jcc/jjaf132

J Trop Pediatr. 2025 Aug 8;71(5):fmaf034. doi: 10.1093/tropej/fmaf034.

ABSTRACT

The World Health Organization (WHO) recommends Xpert® MTB/RIF (Xpert) and its advanced version, Xpert® MTB/RIF Ultra (Xpert Ultra), as first-line diagnostic tests for detecting pulmonary tuberculosis (PTB) and rifampicin resistance in children suspected of having the disease. Respiratory specimens (gastric lavage/bronchoalveolar lavage/sputum/endotracheal aspirate) obtained from 116 children with presumptive PTB were simultaneously processed using liquid medium culture, Xpert assay, and Xpert Ultra assay. Among the specimens from 116 children, six were excluded due to culture contamination (n = 5) or error in Xpert Ultra results (n = 1). Among the remaining 110 specimens, 20 were positive by liquid culture. The former and latter, of the two comparator tests gave a sensitivity of 90% and 95%, respectively. The respective specificity was 93.3% and 88.9%. Xpert Ultra showed a statistically significant slightly higher sensitivity than Xpert. Xpert Ultra showed slightly higher sensitivity than Xpert, with a minimal loss in specificity, partly due to the inclusion of trace results, which help detect paucibacillary cases.

PMID:40795255 | DOI:10.1093/tropej/fmaf034

Genetics. 2025 Aug 7:iyaf158. doi: 10.1093/genetics/iyaf158. Online ahead of print.

ABSTRACT

Testing inferred haplotype genealogies for association with phenotypes has been a longstanding goal in human genetics given their potential to detect association signals driven by allelic heterogeneity – when multiple causal variants modulate a phenotype – in both coding and noncoding regions. Recent scalable methods for inferring locus-specific genealogical trees along the genome, or representations thereof, have made substantial progress towards this goal; however, the problem of testing these trees for association with phenotypes has remained unsolved due to the growth in the number of clades with increasing sample size. To address this issue, we introduce several practical improvements to the kalis ancestry inference engine, including a general optimal checkpointing algorithm for decoding hidden Markov models, thereby enabling efficient genome-wide analyses. We then propose LOCATER, a powerful new procedure based on the recently proposed Stable Distillation framework, to test local tree representations for trait association. Although LOCATER is demonstrated here in conjunction with kalis, it may be used for testing output from any ancestry inference engine, regardless of whether such engines return discrete tree structures, relatedness matrices, or some combination of the two at each locus. Using simulated quantitative phenotypes, our results indicate that LOCATER achieves substantial power gains over traditional single marker testing, ARG-Needle, and window-based testing in cases of allelic heterogeneity, while also improving causal region localization. These findings suggest that genealogy-based association testing will be a fruitful approach for gene discovery, especially for signals driven by multiple ultra-rare variants.

PMID:40795253 | DOI:10.1093/genetics/iyaf158

J Gerontol B Psychol Sci Soc Sci. 2025 Aug 7:gbaf151. doi: 10.1093/geronb/gbaf151. Online ahead of print.

ABSTRACT

OBJECTIVES: Recent studies suggest that the association between social participation and mental health may change with age, although the direction of this relationship is unclear. While some suggest that the mental health benefits of social participation decline with age, others argue they become more important in later life. In this paper, we suggest a context-dependent divergence in aging trajectories: whereas urban older adults continue to gain mental health benefits from social participation, their rural counterparts gradually stop deriving such benefits over time.

METHODS: We drew on four waves of the China Health and Retirement Longitudinal Study (CHARLS, 2011-2018; N = 16,233; 53,056 person-years) to examine how social participation shapes depressive symptoms among adults aged 45 and older. Growth curve models were employed to assess the age-related trajectories of the effects of social participation on depressive symptoms, and interaction terms were introduced to analyze urban-rural differences.

RESULTS: A significant three-way interaction (Informal Social Participation × Rural × Age) revealed that the mental health benefits of informal social participation increased with age among urban older adults but gradually declined among their rural counterparts. This divergence became statistically significant at around age 60 and continued to widen thereafter, indicating a growing urban advantage in the protective effects of informal engagement over time.

DISCUSSION: These findings suggest that the mental health benefits of social participation change with age in ways shaped by residential context, highlighting the need to consider how urban and rural environments differently influence aging trajectories.

PMID:40795235 | DOI:10.1093/geronb/gbaf151